guardrails

RiskKernel is an open-source, self-hosted reliability runtime for AI agents. It adds hard budgets, kill switches, crash-resumable runs, human approval gates, and OpenTelemetry export, with support for OpenAI, Anthropic, and existing agent stacks.

Local guardrails for AI coding agents that intercept destructive actions before they execute, now extended to Git hooks for commit and push enforcement.

Klent is an AI agent guardrails product that sits between agents and their tools, letting teams allow, deny, pause, rewrite, or redirect tool calls with policies, human approval flows, and audit trails.

Go packages for building agents in Go, with a streaming runner, tool dispatch, guardrails, compaction, provider adapters, and verified completion helpers.

Local-first governance layer for AI systems that monitors prompts and responses to block secrets, PII, and runaway LLM spending before requests leave the machine.

A Blue41 case study on how a banking AI assistant could be abused through indirect prompt injection, and what mitigation layers help reduce the risk.

A Python filter layer for LLM apps that evaluates responses against a Lean-verified Scherf logic backend and can pass, flag, correct, or block output.